Chengxi Li
Artificial Intelligence · 2021
A researcher in the Science corpus: 2 papers; trusts 36 researchers and is trusted by 5 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 35 citations into it; #23,070 of 35,345 by trust here, #17,412 by citations
- Signal Processing — 28 citations into it; #4,792 of 7,572 by trust here, #2,911 by citations
- Generative Models — 22 citations into it; #1,357 of 1,956 by trust here, #1,287 by citations
- Computer Vision and Pattern Recognition — 19 citations into it
- Speech & Audio — 19 citations into it; #601 of 1,076 by trust here, #579 by citations
- Natural Language Processing — 11 citations into it
- Statistical and Nonlinear Physics — 11 citations into it
- Probabilistic & Bayesian Methods — 8 citations into it
Whom Chengxi Li trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Pascal Vincent
- Kaiming He
- Geoffrey E. Hinton
- Diederik P. Kingma
- Yoshua Bengio
- Alex Krizhevsky
- Jonathan Ho
- Jascha Narain Sohl-Dickstein
- Yang Song
- Ashish Vaswani
Who trusts Chengxi Li overall
- Rongjie Huang
- Yi Ren
- Zhou Zhao
- Feiyang Chen
- Jinglin Liu
- Songxiang Liu
- Luping Liu
- Hyeong-Seok Choi
- Tomer Amit
Papers from Chengxi Li's perspective
Ordered by how strongly the researchers Chengxi Li trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- GENERATIVE ADVERSARIAL NETS
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Learning Multiple Layers of Features from Tiny Images
Their papers
- DiffSinger: Diffusion Acoustic Model for Singing Voice Synthesis (2021) — 32 citations
- DiffSinger: Singing Voice Synthesis via Shallow Diffusion Mechanism (2021) — 362 citations